> ## Documentation Index > Fetch the complete documentation index at: https://docs.memanto.ai/llms.txt > Use this file to discover all available pages before exploring further. # Expiry Policy > Configure automatic expiration for temporary memories. # Expiry Policy The Expiry Policy page provides fine-grained control over when short-term or session-scoped memories should automatically decay or be removed from the active context window. As your agent runs continuously, it accumulates conversational context, ephemeral observations, and temporary facts that lose relevance over time. Left unchecked, this bloats the context window and increases API costs. The Expiry Policy system solves this by letting you define decay rules based on memory types (e.g., keeping core facts forever while aging out simple events after 7 days). This page is your dashboard for tuning that behavior, previewing its effects, and cleaning up stale data. From this interface, you can: * **View and edit retention rules**: Define how long specific memory types (like observations or events) are retained. * **Load presets**: Quickly apply shipped configuration bundles for common expiration strategies. * **Run sweeps and purge**: Preview what will expire, apply sweeps, or permanently destroy already-expired memories.

### Learn more To avoid duplicating the technical mechanics here, please refer to the following detailed guides: * For the underlying concepts and how decay works, see the [Memory Lifecycle](/reference/memory-lifecycle) reference. * To manage policies from the terminal, refer to the [`memanto policy`](/cli/policy/show) CLI documentation. * For programmatic access, see the [Expiry Policy API](/api-reference/policy/get-policy) endpoints.